Urban travel time reliability at different traffic conditions

Zheng, Fangfang; Li, Jie; Zuylen, Henk J van; Liu, Xiaobo; Yang, Hongtai

doi:10.1080/15472450.2017.1412829

Cited by 30 publications

(11 citation statements)

References 21 publications

(21 reference statements)

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“…New information technology has also brought about the major interest in the privacy aspect of new location-based services in tourism [100]. Additional important concerns in non-environmental mode decision priorities include reliability, which primarily refers to a combination of route choice and departure time [101] and reputation, as a decision-making dimension closely related to perceived quality of the service [102]. Availability is an important non-environmental travel mode decision priority, which is thought to be higher the closer to home one travels, and therefore essential, also important for sustainable travel and tourism [4].…”

Section: Hypothesis 1: Unwillingness To Do Anything About the Environmentioning

confidence: 99%

Sustainable Travel Decision-Making of Europeans: Insights from a Household Survey

Nikolić

Pantić

Paunović³

et al. 2021

Sustainability

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The purpose of this study is to research the antecedents of the sustainable travel decision-making of European travelers and thereby identify important lessons for the transition towards sustainable travel and tourism. The study is based on data collected through a representative survey, conducted in five European countries, with a sample of n = 5024 respondents. The results of descriptive statistics, EFA (Exploratory Factor Analysis) and FA (Factor Analysis) are presented in order to explore sustainable travel decision-making through environmental (policy-related and personal) attitudes and travel mode decision priorities in the European context. Furthermore, the study provides new evidence regarding the under-researched phenomenon of the attitude–behavior gap by presenting a model for the sustainability-oriented decision-making of travelers, including attitudes and travel mode priorities as antecedents. The results confirm the existence of moral licensing in travel decision-making, thereby extending the relevance of this theory into travel and tourism, which has not been done before. The denial of environmental issues is also being researched as regards its interaction with positive environmental attitudes, environmental travel mode priorities and non-environmental travel priorities, thereby advancing our understanding of the interplay between these categories. The interplay between the four categories furthers our understanding of the perplexity of travelers in terms of sustainable travel decision-making.

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Section: Hypothesis 1: Unwillingness To Do Anything About the Environmentioning

confidence: 99%

Sustainable Travel Decision-Making of Europeans: Insights from a Household Survey

Nikolić

Pantić

Paunović³

et al. 2021

Sustainability

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“…The attributes extracted from the data are the nodes’ location, length of links, categories of links, and the links’ end coordinates. The travel time of the road section is a crucial parameter to understand the behavior of traffic (Zheng et al 2018 ). We calculate travel time considering the category (which guides speed limit) and length of a road section.…”

Section: Methodsmentioning

confidence: 99%

Assessing the interplay between travel patterns and SARS-CoV-2 outbreak in realistic urban setting

et al. 2021

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Background The dense social contact networks and high mobility in congested urban areas facilitate the rapid transmission of infectious diseases. Typical mechanistic epidemiological models are either based on uniform mixing with ad-hoc contact processes or need real-time or archived population mobility data to simulate the social networks. However, the rapid and global transmission of the novel coronavirus (SARS-CoV-2) has led to unprecedented lockdowns at global and regional scales, leaving the archived datasets to limited use. Findings While it is often hypothesized that population density is a significant driver in disease propagation, the disparate disease trajectories and infection rates exhibited by the different cities with comparable densities require a high-resolution description of the disease and its drivers. In this study, we explore the impact of creation of containment zones on travel patterns within the city. Further, we use a dynamical network-based infectious disease model to understand the key drivers of disease spread at sub-kilometer scales demonstrated in the city of Ahmedabad, India, which has been classified as a SARS-CoV-2 hotspot. We find that in addition to the contact network and population density, road connectivity patterns and ease of transit are strongly correlated with the rate of transmission of the disease. Given the limited access to real-time traffic data during lockdowns, we generate road connectivity networks using open-source imageries and travel patterns from open-source surveys and government reports. Within the proposed framework, we then analyze the relative merits of social distancing, enforced lockdowns, and enhanced testing and quarantining mitigating the disease spread. Scope Our results suggest that the declaration of micro-containment zones within the city with high road network density combined with enhanced testing can help in containing the outbreaks until clinical interventions become available.

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“…Installing a road-side unit (RSU) and several onboard units (OBU) on cars and monitoring traffic through modern means of control will be able to demonstrate the usefulness and need for an intelligent traffic management system, and also the need for According to the results obtained, the congestion location is a problem generated by the lack of right-of-way priorities to avoid the area, but also a poor road management that starts from the main boulevards with a higher flow of cars. In a first phase, the proposed solution is a topical one based on the current infrastructure [34]. The future model for implementation also includes a practical part of traffic based on the use of devices for traffic management and communication technologies such as V2X, V2I, V2V, and DSRC [35,36].…”

Section: Traffic Flow Solution and Three-dimensional Projectionmentioning

confidence: 99%

Traffic Flow Density Model and Dynamic Traffic Congestion Model Simulation Based on Practice Case with Vehicle Network and System Traffic Intelligent Communication

2020

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The massive increase in the number of vehicles has set a precedent in terms of congestion, being one of the important factors affecting the flow of traffic, but there are also effects on the world economy. The studies carried out so far try to highlight solutions that will streamline the traffic, as society revolves around transportation and its symmetry. Current research highlights that the increased density of vehicles could be remedied by dedicated short-range communications (DSRC) systems through communications of the type vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I) or vehicle-to-everything (V2X). We can say that wireless communication technologies have the potential to significantly change the efficiency and road safety, thus improving the efficiency of transport systems. An important factor is to comply with the requirements imposed on the use of vehicle safety and transport applications. Therefore, this paper focuses on several simulations on the basis of symmetry models, implemented in practical cases in order to streamline vehicle density and reduce traffic congestion. The scenarios aim at both the communication of the vehicles with each other and their prioritization by the infrastructure, so we can have a report on the efficiency of the proposed models.

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Urban travel time reliability at different traffic conditions

Cited by 30 publications

References 21 publications

Sustainable Travel Decision-Making of Europeans: Insights from a Household Survey

Sustainable Travel Decision-Making of Europeans: Insights from a Household Survey

Assessing the interplay between travel patterns and SARS-CoV-2 outbreak in realistic urban setting

Traffic Flow Density Model and Dynamic Traffic Congestion Model Simulation Based on Practice Case with Vehicle Network and System Traffic Intelligent Communication

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